Detection of the Tear Meniscus Shape Using Asymmetric Graph-Cuts
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Yedidya, Tamir
Hartley, Richard
Guillon, Jean-Pierre
Kanagasingam, Yogesan
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Institute of Electrical and Electronics Engineers (IEEE Inc)
Abstract
We present a new fully automatic algorithm to evaluate the shape and regularity of the tear meniscus in eye images taken using a slit-lamp after instilling fluorescein. Our method analyzes the meniscus in the corneal and conjunctival areas and detects abnormalities such as conjunctival folds. We use graph-cuts to minimize a cost function to simultaneously produce a segmentation of the meniscus and the best shape prior for the eyelids. The pairwise term is asymmetric in order to capture the global properties of the meniscus and add a sense of direction. We tested our method on 43 images and provide a grading of the quality of the meniscus.
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Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI 2010)
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2037-12-31